Signaling method in an OFDM multiple access system

ABSTRACT

A method for reducing the peak-to-average ratio in an OFDM communication signal is provided. The method includes defining a constellation having a plurality of symbols, defining a symbol duration for the OFDM communication signal, and defining a plurality of time instants in the symbol duration. A plurality of tones are allocated to a particular communication device, and a discrete signal is constructed in the time domain by mapping symbols from the constellation to the time instants. A continuous signal is generated by applying an interpolation function to the discrete signal such that the continuous signal only includes sinusoids having frequencies which are equal to the allocated tones.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 12/171,155, filed Jul. 10, 2008, which is a continuation ofU.S. patent application Ser. No. 09/805,887, filed on Mar. 15, 2001, nowissued as U.S. Pat. No. 7,295,509 on Nov. 13, 2007 which is herebyexpressly incorporated by reference and which claims the benefit of U.S.Provisional Patent Application Ser. No. 60/230,937 filed Sep. 13, 2000,and titled “SIGNALING METHOD IN AN OFDM MULTIPLE ACCESS WIRELESSSYSTEM,” which is also incorporated by reference.

TECHNICAL FIELD

This invention relates to an orthogonal frequency division multiplexing(OFDM) communication system, and more particularly to an OFDMcommunication system for a multiple access communication network.

BACKGROUND

Orthogonal frequency division multiplexing (OFDM) is a relatively wellknown multiplexing technique for communication systems. OFDMcommunication systems can be used to provide multiple accesscommunication, where different users are allocated different orthogonaltones within a frequency bandwidth to transmit data at the same time. Inan OFDM communication system, the entire bandwidth allocated to thesystem is divided into orthogonal tones. In particular, for a givensymbol duration T available for user data transmission, and a givenbandwidth W, the number of available orthogonal tones F is given by WT.The spacing between the orthogonal tones Δ is chosen to be 1/T, therebymaking the tones orthogonal. In addition to the symbol duration T whichis available for user data transmission, an additional period of timeT_(c) can be used for transmission of a cyclic prefix. The cyclic prefixis prepended to each symbol duration T and is used to compensate for thedispersion introduced by the channel response and by the pulse shapingfilter used at the transmitter. Thus, although a total symbol durationof T+T_(c) is employed for transmitting an OFDM symbol, only the symbolduration T is available for user data transmission and is thereforecalled an OFDM symbol duration.

In prior OFDM techniques, an OFDM signal is first constructed in thefrequency domain by mapping symbols of a constellation to prescribedfrequency tones. The signal constructed in the frequency domain is thentransformed to the time domain by an inverse discrete Fourier transform(IDFT) or inverse fast Fourier transform (IFFT) to obtain the digitalsignal samples to be transmitted. In general, symbols of theconstellation have a relatively low peak-to-average ratio property. Forexample, symbols of a QPSK constellation all have the same amplitude.However, after being transformed by the IDFT or IFFT, the resultant timedomain signal samples are the weighted sum of all the symbols, andtherefore generally do not preserve the desirable low peak-to-averageratio property. In particular, the resulting time domain signaltypically has a high peak-to-average ratio.

Existing techniques for implementing OFDM communication systems can behighly inefficient due to the relatively high peak-to-average ratio whencompared with other signaling schemes, such as single carrier modulationschemes. As a result, existing OFDM techniques are not well suited for awireless multiple access communication network with highly mobile usersbecause the high peak-to-average ratio of the transmitted signalrequires a large amount of power at the base station and at the wirelessdevice. The large power requirements result in short battery life andmore expensive power amplifiers for handheld wireless communicationdevices or terminals. Accordingly, it is desirable to provide an OFDMtechnique which reduces the peak-to-average ratio of the signal to betransmitted, while simultaneously taking advantage of the largercommunication bandwidth offered by an OFDM communication system.

SUMMARY

In one aspect of the communication system, power consumption associatedwith generating and transmitting OFDM signals is reduced as compared tothe prior OFDM systems discussed above. The OFDM signaling methodincludes defining a constellation having a plurality of symbols,defining the symbol duration for the OFDM communication signal, anddefining a plurality of time instants in the symbol duration. In a givensymbol duration, a plurality of tones in the symbol duration areallocated to a particular transmitter and the signal to be transmittedis represented by a vector of data symbols from the symbolconstellation. The symbols are first directly mapped to the prescribedtime instants in the symbol duration. A continuous signal is thenconstructed by applying continuous interpolation functions to the mappedsymbols such that the values of the continuous signal at the prescribedtime instants are respectively equal to the mapped symbols and thefrequency response of the continuous signal only contains sinusoids atthe allocated tones. Finally the digital signal, which is to betransmitted, consists of samples of the continuous signal.Alternatively, the digital signal can be generated directly by applyingdiscrete interpolation functions to the mapped symbols. As symbols fromthe constellation generally have good peak-to-average ratio property,proper choices of allocated frequency tones, prescribed time instantsand interpolation functions can result in a minimized peak-to-averageratio of the continuous function and the digital signal samples.

In one implementation the method of directly generating the digitalsignal samples is to multiply the symbol vector consisting of symbols tobe transmitted with a constant matrix, where the constant matrix isdetermined by the allocated frequency tones and the prescribed timeinstants. The matrix can be precomputed and stored in a memory.

In one aspect, a transmitter associated with the communication system isallocated a number of contiguous tones and the prescribed time instantsare equally-spaced time instants over the entire OFDM symbol duration.

In another aspect, the transmitter is allocated a number ofequally-spaced tones and the prescribed time instants are equally-spacedtime instants over a fraction of the OFDM symbol duration.

In the above aspects, in addition to the general method, the digitalsignal samples can be constructed by expanding the mapped symbols to aprescribed set of time instants from minus infinity to plus infinity andinterpolating the expanded set of the mapped symbols with a sincfunction. Equivalently, the digital signal samples can also be generatedby a series of operations including discrete Fourier transformation,zero insertion, and inverse discrete Fourier transformation.

To further reduce the peak-to-average ratio of the digital signalsamples obtained through interpolation, when symbols of theconstellation are mapped to the prescribed time instants, theconstellations used by two adjacent time instants are offset by π/4.

In another aspect of the system, the real and the imaginary componentsof the resultant digital sample vector are cyclically offset before thecyclic prefix is added. In yet another aspect of the communicationsystem, the intended transmitter is allocated more tones than the numberof symbols to be transmitted. Symbols of the constellation are directlymapped to prescribed equally-spaced time instants. The digital signalsamples are constructed by expanding the mapped symbols to a prescribedset of time instants from minus infinity to plus infinity andinterpolating the expanded set of the mapped symbols with a functionwhose Fourier transformation satisfies the Nyquist zero intersymbolinterference criterion, such as raised cosine functions. The digitalsignal samples can also be generated by a series of operations includingdiscrete Fourier transformation, windowing, and inverse discrete Fouriertransformation.

The details of one or more embodiments of the invention are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the invention will be apparent from thedescription and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram of an OFDM system.

FIG. 2A is a block diagram of an interpolation system used by the OFDMsystem of FIG. 1.

FIG. 2B is a block diagram of another interpolation system used by theOFDM system of FIG. 1.

FIG. 3A is a graph showing symbols mapped to prescribed time instants inthe time domain according to the OFDM technique implemented by thesystem of FIG. 1.

FIG. 3B is a graph showing the frequency domain response of the graph ofFIG. 3B.

FIG. 4A shows an implementation technique for producing a digital signalsample vector using time domain symbol mapping in the case where theallocated tones are contiguous.

FIG. 4B is a block diagram showing a communication system for producinga digital signal sample vector in the case where the allocated frequencytones are contiguous.

FIG. 4C is a graph showing the mapping of the symbols to the prescribedtime instants, the expansion of the mapped symbols, and the use of asinc function to interpolate the expanded symbols.

FIG. 4D is a graph showing the large peak-to-average ratio of theresulting digital signal sample vector when the symbols are mapped inthe frequency domain in the prior OFDM systems.

FIG. 4E is a graph showing the reduced peak-to-average ratio of theresulting digital signal sample vector when the symbols are mapped inthe time domain using the technique of FIGS. 4A-4C.

FIG. 5A shows another implementation technique for producing the digitalsignal sample vector using time domain symbol mapping in the case wherethe allocated tones are equally spaced in frequency.

FIG. 5B is a block diagram showing a communication system for producinga digital signal sample vector in the case where the allocated frequencytones are equally spaced.

FIG. 5C is a graph showing the mapping of the symbols to the prescribedtime instants, the expansion of the mapped symbols, and the use of asinc function to interpolate the symbols.

FIG. 5D is a graph showing the reduced peak-to-average ratio of theresulting digital signal sample vector when the symbols are mapped inthe time domain using the technique of FIGS. 5A-5C.

FIG. 6 is a graph showing π/4 symbol rotation.

FIG. 7 shows the use of a cyclic shift of the real and imaginary signalcomponents.

FIG. 8A is a graph showing application of a windowing function in thefrequency domain to further reduce the peak-to-average ratio.

FIG. 8B is a block diagram showing a technique using more tones than thenumber of symbols to be transmitted for producing a digital signalsample vector.

FIG. 8C is a graph showing the use of an interpolation functioncorresponding to the window function of FIG. 8B to the symbols mapped tothe prescribed time instants.

FIG. 8D is a graph showing the reduced peak-to-average ratio of theresulting digital signal sample vector when the symbols are mapped inthe time domain using the technique of FIGS. 8A-8C.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

Referring to FIG. 1, an orthogonal frequency division multiplexing(OFDM) communication system 10 is shown. OFDM communication system 10receives a first constellation of symbols {B_(i)} 12 and provides thesymbols to a symbol-to-symbol mapping circuit 14, that produces a secondconstellation of complex symbols {C_(i)} 16. The complex symbols 16represent data or a stream of data to be transmitted by the OFDMcommunication system, and may be chosen from a variety of symbolconstellations including, but not limited to phase shift keying (PSK)and quadrature amplitude modulation (QAM) symbol constellations. Thesymbol-to-symbol mapping performed by the mapping circuit 14 is anoptional step performed by the OFDM communication system 10.

Next, a time instant mapping circuit 18 maps each complex symbol 16 to aprescribed time instant within a given OFDM symbol duration. The mappingoperation is performed in the time domain such that the mapping circuit18 generates a discrete signal of mapped symbols within the time domainsymbol duration. The output of the mapping circuit 18 is provided to aninterpolation circuit 20, that produces a series of digital signalsamples {S_(i)} 22. The digital signal samples 22 are formed by samplinga continuous signal, which is constructed by applying one or morepredetermined continuous interpolation functions to the mapped complexsymbols 19. Alternatively, the digital signal samples 22 are formed bydirectly applying one or more predetermined discrete interpolationfunctions to the mapped complex symbols 19. When using the technique ofapplying discrete interpolation functions, no intermediate continuoussignal is generated and the step of sampling the continuous signal isnot necessary. The operation of the interpolation circuit 20 isdescribed in greater detail below. A cyclic prefix circuit 24 receivesthe series of digital signal samples 22 from the interpolation circuit20 and prepends a cyclic prefix to the digital signal samples 22. Thecyclic prefix circuit 24 operates to copy and prepend the last portionof the digital signal sample vector S 22 to the beginning of the OFDMsymbol duration. The resulting digital signal samples 22 with theprepended cyclic prefix are converted to an analog signal by a digitalto analog converter 28. The resulting analog signal is further processedby a pulse shaping filter 30, the output of which is modulated to acarrier frequency, and amplified by a power amplifier unit 32 fortransmission through an antenna 34.

In one implementation of the OFDM communication system 10, thesymbol-to-symbol mapping circuit 14, the time instant mapping circuit18, the interpolation circuit 20, and the cyclic prefix circuit 24 areimplemented in a digital signal processor (DSP) 26, and may include acombination of hardware modules and/or software modules. These circuits14, 18, 20, and 24 can also be implemented as separate discrete circuitswithin the OFDM communication system 10.

The details of the interpolation circuit 20 are shown in FIG. 2A. Theinterpolation circuit 20 includes an interpolation function module 21that applies one or more continuous interpolation functions to thediscrete signal of mapped symbols 19 to generate a continuous signal inwhich signal variation between adjacent symbols is minimized. Thus, thecontinuous signal has a low peak-to-average ratio. The interpolationfunctions may be precomputed and stored in an interpolation functionmemory 23 connected to the interpolation function module 21. A frequencytone and time instant allocation circuit 27 is connected to theinterpolation function memory 23 and defines an allocated tone setselected from frequency tones distributed over a predetermined bandwidthassociated with the OFDM communication system 10. The allocated tone setis then provided to the interpolation function memory 23. The frequencytone and time instant allocation circuit 27 also defines the prescribedtime instants distributed over the time domain symbol duration, whichcan also be stored in the interpolation function memory 23 for use bythe interpolation function module 21 as well as other modules within theDSP 26. The interpolation circuit 20 also includes a sampling circuit 25for receiving and sampling the continuous signal at discrete timeinstants distributed over the time domain symbol duration to generatethe vector of digital signal samples 22. Alternatively, in FIG. 2B theinterpolation function module 21 applies one or more discreteinterpolation functions to the discrete signal of mapped symbols 19 todirectly generate the digital signal sample vector 22, in which case thesampling circuit 25 (of FIG. 2A) is not needed. Through applying thediscrete interpolation functions, the interpolation function module 21effectively combines the processing steps of applying the continuousinterpolation functions and sampling the intermediate continuous signal.

FIG. 3A graphically depicts the signal processing steps performed by thevarious circuits of the DSP 26. More specifically, FIG. 3A shows theconstruction of the signal to be transmitted in a given OFDM time domainsymbol duration 40. The time domain symbol duration 40 is a timeinterval from 0 to T. For purposes of the following description, theOFDM symbol duration T does not include the cyclic prefix. The signal tobe transmitted in the symbol duration 40 is represented by complexsymbols C₁, C₂, C₃, . . . , C_(M) 16 that are mapped to the prescribedtime instants, where M denotes the number of symbols to be transmittedin the symbol duration 40.

In one implementation, the OFDM communication system 10 is a multipleaccess communication system where the entire bandwidth available to alltransmitters within the system is divided into F orthogonal frequencytones, ƒ₁, ƒ₂, . . . , ƒ_(F). In the given symbol duration 40, aparticular transmitter operating within a multiple access communicationsystem is allocated M frequency tones ƒ_(i(1)), ƒ_(i(2)), . . . ,ƒ_(i(M)), which is a subset of ƒ₁, ƒ₂, . . . , ƒ_(F), (the total numberof frequency tones) in order to transmit the signal. As part of thisimplementation, the number of tones allocated to a particulartransmitter is equal to the number of symbols to be transmitted by thattransmitter. Later in FIG. 8A, the number of allocated tones can begreater than the number of symbols to be transmitted. The remainingfrequency tones can be used by other transmitters within thecommunication system. This technique allows OFDM communication system 10to operate as a multiple access communication system.

The complex data symbols C₁, C₂, C₃, . . . , C_(M) 16 are first mappedto t₁, t₂, t₃, . . . , t_(M), respectively, where t₁, t₂, t₃, . . . ,t_(M) are M prescribed time instants within the time domain symbolduration 40. The mapping operation generates a discrete signal of mappedsymbols. It should be noted that the number of prescribed time instantsis equal to the number of symbols M to be transmitted. As describedabove, the symbol mapping occurs in the time domain. Continuousinterpolation functions 42 are then applied to the discrete signal ofmapped symbols 16 to generate a continuous function CF(t) for t in thetime interval from 0 to T.

The interpolation functions 42 are constructed such that the values ofthe continuous function CF(t) at time instants t₁, t₂, t₃, . . . , t_(M)are respectively equal to C₁, C₂, C₃, . . . , C_(H) and the frequencyresponse of the continuous function CF(t) contains only sinusoids at theallocated tones. Therefore, CF(t) is constructed as

${{CF}(t)} = {\sum\limits_{k = 1}^{M}{A_{k}{\mathbb{e}}^{J\; 2\pi\; f_{i{(k)}}t}}}$where J=√{square root over (−1)} and coefficients A_(k) are given by

${{\begin{bmatrix}A_{1} \\\vdots \\A_{M}\end{bmatrix} = \begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}t_{1}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}t_{1}} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}t_{M}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}t_{M}}\end{bmatrix}}\quad}^{- 1}\begin{bmatrix}C_{1} \\\vdots \\C_{M}\end{bmatrix}$Thus, each coefficient A_(k) is generated by multiplying a matrix ofpredetermined sinusoids with the single column of data symbols C₁, C₂,C₃, . . . , C_(M) 16.

FIG. 3B shows the frequency response of the continuous function CF(t).More specifically, FIG. 3B shows that the frequency response of thecontinuous function is non-zero only at the allocated frequency tonesƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M)), and is zero at all other frequencytones.

The output of the DSP 26 is a vector of digital signal samples S 22,which are the samples of the continuous function CF(t) at discrete timeinstants 0, T/N, 2T/N, . . . , T(N−1)/N, that is, S₁=CF(0), S₂=CF(T(N),S₃=CF(2T/N), . . . , S_(N)=CF(T(N−1)/N), where N is the number ofdiscrete time instants in the vector of digital signal samples 22. In ageneral form, t₁, . . . , t_(M) may not necessarily be equal to any ofthe time instants 0, T/N, 2T/N . . . , T(N−1)/N. Therefore, while thedigital signal samples S 22 may occur at the time instants t₁, . . . ,t_(M), the OFDM communication system 10 does not require that the timeinstants 0, T/N, 2T/N . . . , T(N−1)/N be equal to t₁, . . . , t_(M).

In another implementation of OFDM communication system 10, the digitalsignal samples S 22 may be generated by the DSP 26 by directlymultiplying a matrix of precomputed sinusoidal waveforms Z, operating asdiscrete interpolation functions, with the discrete signal of mappedsymbols C in order to satisfy the transformation function S =ZCaccording to the following:

$\begin{matrix}{S = \begin{bmatrix}S_{1} \\\vdots \\S_{N}\end{bmatrix}} \\{= {\begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}0} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}0} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}T\frac{N - 1}{N}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}T\frac{N - 1}{N}}\end{bmatrix}\begin{bmatrix}A_{1} \\\vdots \\A_{M}\end{bmatrix}}} \\{= \begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}0} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}0} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}T\frac{N - 1}{N}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}T\frac{N - 1}{N}}\end{bmatrix}} \\{\begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}t_{1}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}t_{1}} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}t_{M}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}t_{M}}\end{bmatrix}^{- 1}\begin{bmatrix}C_{1} \\\vdots \\C_{M}\end{bmatrix}} \\{= {ZC}}\end{matrix}$where C represents the symbol vector, and the matrix Z represents theproduct of the two matrices in the second line of the above equation.Each column (i) of matrix Z represents the interpolation function 42 ofa corresponding symbol C_(i) to generate the digital signal samples S22. As such, the matrix Z can be pre-computed and stored in theinterpolation function memory 23 of the interpolation circuit 20 (FIG.2B). The interpolation circuit 20 then applies the discreteinterpolation functions 42 defined by the matrix Z to the discretesignal of mapped complex symbols C 16 in order to satisfy the criteriaof S=ZC and to generate the vector of digital signal samples 22.

The purpose of constructing the signal in the time domain is to directlymap the symbols 16, which have a desirable low peak-to-average ratioproperty, to the prescribed time instants within the symbol duration 40.Appropriate interpolation functions 42 are selected to obtain thecontinuous function CF(t) and the digital signal samples 22 such thatthe desirable low peak-to-average ratio property of the symbols 16 issubstantially preserved for the continuous function and for the digitalsignal samples 22. The peak-to-average ratio property of the resulting(interpolated) continuous function CF(t) and the digital signal samples22 is dependent upon the interpolation functions 42, the choice ofallocated frequency tones ƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M)) from theset of tones, and the prescribed time instants t₁, . . . , t_(M).

Referring to FIG. 4A, one implementation of the OFDM communicationsystem 10 allocates tones ƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M)) to thetransmitter associated with the communication system that are a subsetof contiguous tones in the tone set ƒ₁, ƒ₂, . . . , ƒ_(F). Therefore,ƒ_(i(k))=ƒ₀+(k−1)Δ, for k=1, . . . , M, where M is the number ofsymbols. If the OFDM communication system 10 is a multiple accesssystem, each transmitter associated with the communication system isallocated a non-overlapping subset of frequency tones. For purposes ofdescription, let f₀=0. The construction for the other cases where f₀≠0can be similarly obtained.

Complex symbols C₁, . . . , C_(M) 16 are mapped in the time domain tothe following time instants t_(k)=(k−1)T/M, for k=1, . . . , M. As partof this implementation, the prescribed time instants t₁, . . . , t_(M)are equally-spaced time instants uniformly distributed over the entireOFDM symbol duration 40 as shown in the first time domain graph of FIG.4A. Given the choice of the allocated frequency tones and prescribedtime instants, the matrix Z, which is used to generate the digitalsignal samples S as discussed in FIGS. 3A-3B, can be simplified to

$Z = {{{\frac{1}{M}\begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}0} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}0} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}T\frac{N - 1}{N}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}T\frac{N - 1}{N}}\end{bmatrix}}\begin{bmatrix}{\mathbb{e}}^{{- J}\; 2\pi\; f_{i{(1)}}t_{1}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}t_{M}} \\\vdots & \; & \vdots \\{\mathbb{e}}^{{- J}\; 2\pi\; f_{i{(M)}}t_{1}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}t_{M}}\end{bmatrix}}.}$

The second time domain graph of FIG. 4A shows the resulting digitalsignal sample vector S 22 after the interpolation circuit 20 applies theinterpolation functions 42 defined by the matrix Z to the complexsymbols 16 according to the expression S=ZC. As part of thisimplementation, the sampling module 25 is not generally used as thedigital signal sample vector S 22 is directly generated from thediscrete signal of mapped symbols using the transformation functionS=ZC.

Turning to FIG. 4B, a digital processing system 50 provides anothertechnique for obtaining the vector of digital signal samples S. A DFTcircuit 52 receives a discrete signal of complex data symbols C_(i) andcalculates the frequency responses A₁, . . . , A_(M), at tones ƒ_(i(1)),ƒ_(i(2)), . . . , ƒ_(i(M)), through an M-point discrete Fouriertransform (DFT). The vector [A₁, . . . , A_(M)] 54 output by the DFTcircuit 52 is then expanded to a new vector of length N (the totalnumber of time instants in the discrete signal vector S) by zeroinsertion at block 56. More specifically, this process involves puttingthe k^(th) symbol A_(k) to the i(k)^(th) element of the new vector, fork=1, . . . , M, where f_(i(k)) is the k^(th) tone allocated to thetransmitter, and inserting zeros in all the remaining elements. Finally,an IDFT circuit 58 performs an N-point inverse discrete Fouriertransform on the resulting vector (after zero insertion) to obtain thedigital signal sample vector S. The collective procedure of DFT, zeroinsertion and IDFT is one way of implementing the discrete interpolationfunctions.

Turning to FIG. 4C, another technique for obtaining the digital signalsamples S is shown. For simplicity of description, it is assumed thatthe allocated contiguous tones ƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M)) arecentered at frequency 0. The construction for the other cases where theallocated tones are not centered at frequency 0 can be similarlyobtained. As with FIG. 4A, the prescribed time instants t₁, . . . ,t_(M) are equally-spaced time instants uniformly distributed over theentire OFDM symbol duration 40.

The complex symbols C₁, . . . , C_(M) are first mapped in the timedomain to time instants t₁, . . . , t_(M) respectively. Next, the mappedsymbols C₁, . . . , C_(M) are leftwards and rightwards shifted andreplicated to an expanded set of prescribed time instants, which is asuperset of t₁, . . . , t_(M) and consists of an infinite number ofequally-spaced time instants covering the time interval from −∞ to +∞.This technique creates an infinite series of mapped symbols C. Thecontinuous function CF(t) is then constructed by interpolating theinfinite series of mapped symbols using a sinc interpolation function60. Mathematically, the above steps construct the continuous functionCF(t) as

$\begin{matrix}{{{CF}(t)} = {\sum\limits_{i = 1}^{M}{\left\{ {C_{i}{\sum\limits_{k = {- \infty}}^{\infty}{\sin\mspace{11mu}{c\left( {{t - t_{i} - {kT}},\frac{T}{M}} \right)}}}} \right\}.}}} & 1.\end{matrix}$where sinc(a,b)=sin(πa/b)/(πa/b). The sinc interpolation function 60 canalso be precomputed and stored in the interpolation function memory 23.As discussed in FIG. 3A the digital signal samples S 22 are the samplesof the continuous function CF(t) at time instants 0, . . . , T/N,T(N−1)/N. In FIGS. 4A-4C, if N is a multiple of M, thenS_(1+(k−1)N/M)=C_(k), for k=1, . . . , M. It should be noted that thecontinuous function CF(t) only applies to the symbol duration 40 from 0to T. The use of time interval from −∞ to +∞ is solely for the purposeof mathematically constructing CF(t). The discrete interpolationfunctions, which combine the continuous interpolation functions and thesampling function, can be derived easily from the above description.

For comparison purposes, FIG. 4D illustrates the resultingpeak-to-average ratio for a digital signal sample vector S 62 and itsassociated transmitted OFDM signal 64 produced by symbols 16 where thesignal is constructed in the frequency domain. As described above, thisknown technique of mapping the symbols 16 in the frequency domainproduces a large signal variation in the transmitted OFDM signal 64 andresults in a large peak-to-average ratio.

FIG. 4E illustrates the resulting small signal variation and lowpeak-to-average ratio of the digital signal sample vector S 66associated with the transmitted OFDM signal 68. As will be appreciatedby comparing FIGS. 4D and 4E, mapping the constellation of complexsymbols 16 in the time domain produces an OFDM signal 68 having asignificantly reduced peak-to-average ratio.

FIG. 5A shows a second implementation of the OFDM communication system10, and serves to further generalize the system shown in FIGS. 4A-4C. Aspart of OFDM system 10, tones, ƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M)),allocated to the transmitter associated with the communication system,are a subset of equally-spaced tones in the tone set ƒ₁, ƒ₂, . . . ,ƒ_(F). Therefore, ƒ_(i(k))=ƒ₀+(k−1)LΔ, for k=1, . . . , M, and L is apositive integer number representing the spacing between two adjacentallocated frequency tones. When L=1, this implementation is equivalentto the implementation technique described in FIGS. 4A-4C. For the sakeof description, let f₀=0. The construction for the other cases wheref₀≠0 can be similarly obtained.

In this case where the allocated tones are equally-spaced tones, theconstructed continuous function CF(t) is identical in each of the L timeintervals, [0,T/L), [T/L,2T/L), . . . , and [(L−1)T/L, T/L). As part ofthis technique, symbols C₁, . . . , C_(M) 16 are mapped to the followingtime instants t_(k)=(k−1)T/M/L, for k=1, . . . , M. In thisimplementation, the prescribed time instants t₁, . . . , t_(M) areequally-spaced time instants uniformly distributed over a fraction (1/L)of the symbol duration 70. As a comparison, in the case of allocatedcontiguous tones (FIG. 4A), the prescribed time instants areequally-spaced and distributed over the entire symbol duration, asdiscussed with respect to FIG. 4A.

The procedure for obtaining the digital signal samples S 22 described inFIG. 4A can also be applied with respect to FIG. 5A. More specifically,the digital signal sample vector S is the product of matrix Z (definingthe discrete interpolation functions) and the symbol vector C. Given thechoice of the allocated frequency tones and prescribed time instants,the matrix Z, which is used to generate the digital signal samples 22from the discrete signal of mapped symbols, can be simplified to thesame formula as in FIG. 4A with the only change in the definition ofƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M)) and t₁, . . . , t_(M).

In FIG. 5B, the procedure of obtaining the digital signal sample vectorS 22 described in FIG. 4B can also be applied to the case of allocatedfrequency tones that are equally spaced tones. More specifically, adigital processing system 100 provides another technique for obtainingthe vector of digital signal samples S. A DFT circuit 102 receives adiscrete signal of complex data symbols C_(i) and calculates thefrequency responses A₁, . . . , A_(M), at tones ƒ_(i(1)), ƒ_(i(2)), . .. , ƒ_(i(M)), through an M-point discrete Fourier transform (DFT). Thevector [A₁, . . . , A_(M)] 104 output by the DFT circuit 102 is thenexpanded to a new vector of length N (the total number of time instantsin the digital signal sample vector S) by zero insertion at block 106.More specifically, this process involves putting the k^(th) symbol A_(k)to the i(k)th element of the new vector, for k=1, . . . , M, wheref_(i(k)) is the k^(th) tone allocated to the transmitter, and insertingzeros in all the remaining elements. Finally, an IDFT circuit 108performs an N-point inverse discrete Fourier transform on the resultingvector (after zero insertion) to obtain the time domain digital signalsample vector S. The collective procedure of DFT, zero insertion andIDFT is one way of implementing the discrete interpolation functions.

FIG. 5C is the counterpart of FIG. 4C, where symbols C₁, . . . , C_(M)are first mapped to t₁, . . . , t_(M) respectively over a fraction (1/L)of the symbol duration 70. The symbol mapping is also performed in thetime domain. Next the mapped symbols C₁, . . . , C_(M) are leftwards andrightwards shifted and replicated to an expanded set of prescribed timeinstants from −∞ to +∞ which creates an infinite series of symbols. Thecontinuous function CF(t) is then constructed by interpolating theinfinite series of mapped symbols with a sinc interpolation function 72.Thus, the continuous function CF(t) includes the digital signal samplesmapped to the prescribed time instants as well as digital sample pointsbetween the prescribed time instants. Mathematically, the above stepsconstruct the continuous function as

$\begin{matrix}{\;{{{CF}(t)} = {\sum\limits_{i = 1}^{M}{\left\{ {C_{i}{\sum\limits_{k = {- \infty}}^{\infty}{\sin\mspace{11mu}{c\left( {{t - t_{i} - {{kT}\frac{1}{L}}},{\frac{T}{M}\frac{1}{L}}} \right)}}}} \right\}.}}}} & 2.\end{matrix}$With continued reference to FIG. 5C, each sinc interpolation function 72is narrower and therefore decays faster than the sinc interpolationfunction 60 shown in FIG. 4C. The sinc interpolation function 72 canalso be precomputed and stored in the interpolation function memory 23for use by the interpolation function module 21. The digital samplevector S 22 can be obtained in the same technique shown in FIG. 4C. InFIGS. 5A and 5C, if N is a multiple of ML, thenS_(1+(k−1)N/M/L+(j−1)N/L)=C_(k), for k=1, . . . , M, and j=1, . . . , L.The discrete interpolation functions, which combine the continuousinterpolation functions and the sampling function, can be derived easilyfrom the above description.

FIG. 5D illustrates the resulting small signal variation and lowpeak-to-average ratio of the digital signal sample vector S 74associated with the transmitted OFDM signal 76. As will be appreciatedby comparing FIGS. 4D and 5D, mapping the constellation of complexsymbols 16 in the time domain produces an OFDM signal 76 having asignificantly lower peak-to-average ratio.

Referring now to FIG. 6, a π/4 symbol rotation technique is used tofurther reduce the peak-to-average ratio of the transmitted OFDM signal.At an OFDM symbol duration, if symbols B₁, . . . , B_(M) of theconstellation are to be transmitted, symbols B₁, . . . , B_(M) aremapped to another block of complex symbols C₁, . . . , C_(M), where eachodd number symbol remains unchanged and each even number symbol is phaserotated by π/4. For example, if symbols B₁, . . . , B_(M) belong to aQPSK constellation {0, π/2, π, π3/2}, the odd number symbols C_(k) stillbelong to the same QPSK constellation, while after being phase rotatedthe even number symbols C_(k) belong to another QPSK constellation {π/4,π3/4, π5/4, π7/4}. Symbols C₁, . . . , C_(M) are then used to constructthe digital signal samples 22 in the time domain as described above withrespect to FIGS. 3A-5C.

With reference to FIG. 7, another technique for reducing thepeak-to-average ratio is shown, which introduces a cyclic offset of thereal and imaginary signal components. This technique involves a firststep of offsetting the imaginary components of the digital signalsamples S 22, which have been generated using the technique of FIGS.3A-5C, by an integer number of samples. If necessary, the technique theninvolves a second step of adjusting the timing by a fraction of a sampleperiod between the real and the imaginary signal components in thetransmit path.

At an OFDM symbol duration, if the digital signal samples S₁, S₂, . . ., S_(N) have been obtained using the method as described in FIGS. 3A-5C,the digital signal sample vector S is then mapped to another vector S′as follows. The real component of digital signal sample S′_(k) is equalto that of digital signal sample S_(k). The imaginary component ofdigital signal sample S′_(k) is equal to that of digital signal sampleS_(j) where index j=(k+d−1) mod N+1, for k=1, . . . , N, with modrepresenting a module operation. The parameter d is an integerrepresenting the cyclic offset, in terms of number of samples, betweenthe real and imaginary components.

In one implementation, the value of d is determined by

$\frac{N}{2{LM}},$where L is discussed in FIG. 5A. In one aspect of this technique, d ischosen to be close to

$\frac{N}{2{LM}}.$For example, d can be the integer closest to

$\frac{N}{2{LM}},$the largest integer not greater than

$\frac{N}{2{LM}},$or the smallest integer not smaller than

$\frac{N}{2{LM}}.$In one example, d is chosen to be the largest integer not greater than

$\frac{N}{2{LM}}.$This example can be easily extended for other choices of d.

The digital signal sample vector S′ is then passed to the cyclic prefixprepender circuit 24, as shown in FIG. 1. Therefore, the operation ofhalf symbol cyclic shifting is carried out before the operation ofprepending the cyclic prefix, such as that performed by the cyclicprefix circuit 24 of FIG. 1.

Not specifically shown in FIG. 7, when or after the sample vector S′ andthe cyclic prefix are outputted to the digital to analog converter 28,the imaginary components are further delayed by an amount of

${\left( {\frac{N}{2{LM}} - d} \right)\frac{T}{N}},$which is a fraction of a sample period T/N.

As a variation of the technique shown in FIG. 7 (not specificallyshown), another technique for achieving a similar result can be used toeliminate the second step of adjusting timing by a fraction of a sampleperiod between the real and the imaginary signal components in thetransmit path. As part of this technique, the real and the imaginarycomponents of the desired digital signal samples S 22 are generatedseparately as described by the following.

A first series of digital signal samples 22 are generated using thetechnique of FIGS. 3A-5C. The real components of the desired digitalsignal samples 22 are equal to those of the first series of samples. Asecond series of digital signal samples 22 are generated using thetechnique of FIGS. 3A-5C except for the following changes. The imaginarycomponents of the desired digital signal samples are equal to those ofthe second series of samples. In the general method described in FIGS.3, 4A, and 5A, the matrix

$\begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}0} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}0} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\; f_{i{(1)}}T\frac{N - 1}{N}} & \cdots & {\mathbb{e}}^{J\; 2\pi\; f_{i{(M)}}T\frac{N - 1}{N}}\end{bmatrix}\quad$is changed to

${\begin{bmatrix}{\mathbb{e}}^{J\; 2\pi\;{f_{i{(1)}}{({0 - \frac{T}{2{LM}}})}}} & \cdots & {\mathbb{e}}^{J\; 2\pi\;{f_{i{(M)}}{({0 - \frac{T}{2{LM}}})}}} \\\vdots & \; & \vdots \\{\mathbb{e}}^{J\; 2\pi\;{f_{i{(1)}}{({{T\frac{N - 1}{N}} - \frac{T}{2{LM}}})}}} & \cdots & {\mathbb{e}}^{J\; 2\pi\;{f_{i{(M)}}{({{T\frac{N - 1}{N}} - \frac{T}{2{LM}}})}}}\end{bmatrix}\quad}.$

In the block diagram method described with regard to FIG. 4B, anadditional operation is required after zero insertion (block 56) andbefore N-point IDFT (block 58), where each element k in the expandedlength N vector is phase rotated by e^(−J2πƒ) ^(k) ^(T/2LM).

Referring to FIGS. 8A-8D, another technique for further reducing thepeak-to-average ratio is implemented by allocating more frequency tonesthan the number of complex symbols to be transmitted in a symbolduration 40. In FIGS. 3-7, the number of tones allocated to thetransmitter associated with the communication system is equal to thenumber of symbols to be transmitted in a given OFDM symbol duration.Compared with the other techniques described with respect to theprevious figures, the technique of FIGS. 8A-8D requires additionaloverhead of bandwidth to transmit the same number of complex symbols.

For example, if the communication system 10 is allocated M+M_(ex)contiguous frequency tones, ƒ_(i(1)), ƒ_(i(2)), . . . , ƒ_(i(M+Mex)),and M symbols C₁, . . . , C_(M) of the constellation are to betransmitted at an OFDM symbol duration, from the comparison of FIGS. 4Aand 5A, the case of allocated contiguous tones can be easily extended tothe case of allocated equally-spaced tones. As part of thisimplementation of the OFDM communication system 10, M_(ex) is a positivenumber representing the number of excess tones to be used and is assumedto be an even number. Therefore, the allocated tone

${f_{i{(k)}} = {f_{0} + {\left( {k - \frac{M_{ex}}{2} - 1} \right)\Delta}}},$for k=1, . . . , M+M_(ex). For purposes of description, let f₀=0. Theconstruction for the other cases where f₀≠0 can be similarly obtained.

As with the technique described with respect to FIG. 4A, the prescribedtime instants are t_(k)=(k−1)T/M, for k=1, . . . , M, that is, theprescribed time instants t₁, . . . , t_(M) are equally-spaced timeinstants in the symbol duration 40.

As part of this technique shown in FIG. 8A, P(ƒ) is a smooth windowingfunction 90 in the frequency domain, which is non-zero only overinterval [ƒ_(i(1)), ƒ_(i(M+Mex))]. In addition, P(ƒ) 90 also satisfiesthe Nyquist zero intersymbol interference criterion, i.e.,

${\sum\limits_{k = {- \infty}}^{\infty}{P\left( {f - {{kM}\;\Delta}} \right)}} = 1$for any frequency f, where is the spacing between adjacent tones.

FIG. 8B shows the block diagram of the technique. As described above, asymbol-to-symbol mapping is optionally performed to generate a discretesignal of mapped complex symbols C₁, . . . , C_(M), 16. The frequencyresponses A₁, . . . , A_(M) 84 are calculated through an M-pointdiscrete Fourier transform (DFT) of the complex symbols 16 at block 82.At block 86, vector [A₁, . . . , A_(M)] 84 is cyclically expanded to anew vector A′ of length N and windowed with a windowing function 90 asfollows:

-   3.    A′ _(k) =A _(g(k)) *P((k−1)+ƒ ₁)  4-   5.    where index g(k)=mod(k−i(1)−M_(ex)/2, M)+1, for k=1, . . . , N.

At block 88, the digital signal sample vector S is obtained by taking anN-point inverse discrete Fourier transform (IDFT) of the new vector A′.Finally, the cyclic prefix is added by cyclic prefix circuit 24 asdescribed above with regard to FIG. 1.

To provide additional insight to the above signal constructiontechnique, assume that the allocated tones f_(i(1)), f_(i(2))), . . . ,f_(i(M+Mex)) are centered at frequency 0. In FIG. 8C (as with FIG. 4C),symbols C₁, . . . , C_(M) are first mapped to equally-spaced timeinstants in the symbol duration 40, and are then leftwards andrightwards shifted and replicated from −∞ to +∞. What is different fromFIG. 4C is that a different interpolation function 92, which isdetermined by the windowing function 90, is used to generate thecontinuous function,CF(t)=Σ_(i=1) ^(M) C _(i)Σ_(k=−∞) ^(∞) p(t−t ₁ −kT)  6

-   7.    where p(t) 92 is the time domain response of P(ƒ) 90. As with FIG.    4C, the digital signal samples are obtained by letting t=0, T/N, . .    . , T(N−1)/N.

In one exemplary aspect of this technique, if a raised cosine windowingfunction is used, i.e.,

$\begin{matrix}{{P(f)} = \left\{ \begin{matrix}\frac{T}{M} & {if} & {{f} < {\left( {1 - \beta} \right)\frac{M}{2T}}} \\{\frac{T}{2M}\left\{ {1 + {\cos\left\lbrack {\frac{\pi\; T}{\beta\; M}\left( {{f} - \frac{\left( {1 - \beta} \right)M}{2T}} \right)} \right\rbrack}} \right\}} & {if} & {{\left( {1 - \beta} \right)\frac{M}{2T}} \leq {f} \leq {\left( {1 + \beta} \right)\frac{M}{2T}}} \\0 & {if} & {{f} > {\left( {1 + \beta} \right)\frac{M}{2T}}}\end{matrix} \right.} & 8.\end{matrix}$where β=(M_(ex)+2)/M represents the percentage of excess tone overhead,then, the interpolation function p(t) 92 is given by

${p(t)} = {\frac{\sin\left( {\pi\; t\;{M/T}} \right)}{\pi\; t\;{M/T}}{\frac{\cos\left( {{\pi\beta}\; t\;{M/T}} \right)}{1 - {4\beta^{2}t^{2}{M^{2}/T^{2}}}}.}}$As β increases, the interpolation function p(t) 92 decays faster,thereby reducing the probability of having large peak at samples betweent_(i).

FIG. 8D shows the resulting small signal variation and lowpeak-to-average ratio of the digital signal sample vector S 94associated with the transmitted OFDM signal 96. As will be appreciated,mapping the constellation symbols 16 in the time domain produces an OFDMsignal 96 having a significantly lower peak-to-average signal ratio.

A number of embodiments of the invention have been described.Nevertheless, it will be understood that various modifications may bemade without departing from the spirit and scope of the invention.Accordingly, other embodiments are within the scope of the followingclaims.

1. A processor-based apparatus for generating wireless communications,the processor-based apparatus comprising: at least one first circuitconfigured to perform a Discrete Fourier Transform (DFT) on a discretesignal of complex data symbols to obtain a first frequency responsevector of length M; a second circuit configured to perform an N-pointInverse DFT (IDFT) on a second frequency response vector of length N,generated from the first frequency response vector by inserting zerovalue symbols corresponding to tones not allocated to the apparatus, toobtain a vector of digital signal samples; a third circuit configured topre-pend a cyclic prefix to the vector of digital signal samples; and afourth circuit configured to generate a signal representing the vectorof digital signal samples with pre-pended cyclic prefix fortransmission.
 2. The processor-based apparatus of claim 1, wherein thesecond frequency response vector has entries corresponding to one ormore groups of tones allocated to the processor-based apparatus.
 3. Theprocessor-based apparatus of claim 2, wherein the one or more groups oftones allocated to the processor-based apparatus are contiguous.
 4. Theprocessor-based apparatus of claim 2, wherein the one or more groups oftones allocated to the processor-based apparatus comprise non-contiguousgroups.
 5. The processor-based apparatus of claim 4, wherein at leasttwo of the one or more groups comprises contiguous tones within each ofthe at least two groups.
 6. The processor-based apparatus of claim 5,wherein the at least two groups comprise at least two groups with a samenumber of tones.
 7. The processor-based apparatus of claim 4, whereinthe one or more groups comprise at least two groups with a differentnumber of tones.
 8. The processor-based apparatus of claim 4, whereinthe non-contiguous groups of tones comprise equally spaced groups oftones.
 9. The processor-based apparatus of claim 4, wherein thenon-contiguous groups of tones comprise tones separated by tones havingcorresponding zero value symbols in the second frequency responsevector.
 10. The processor-based apparatus of claim 9, wherein thenon-contiguous groups of tones comprise clusters of one or more tonesseparated by tones having corresponding zero value symbols in the secondfrequency response vector.
 11. The processor-based apparatus of claim 1,wherein the first, second, and third circuits comprise a combination ofhardware and software modules.
 12. The processor-based apparatus ofclaim 1, wherein at least one of the first, second, and third circuitscomprises a software module.
 13. The processor-based apparatus of claim1, wherein the fourth circuit comprises: a circuit configured to convertthe vector of digital signal samples to an analog signal.
 14. Theprocessor-based apparatus of claim 13, wherein the fourth circuitfurther comprises: a circuit configured to modulate the analog signal toa carrier frequency for transmission.
 15. The processor-based apparatusof claim 14, wherein the fourth circuit further comprises: a pulsefilter circuit configured to process the analog signal prior tomodulation to the carrier frequency.
 16. The processor-based apparatusof claim 14, further comprising: at least one antenna; and a poweramplifier circuit configured to amplify the analog signal prior totransmission via the at least one antenna.
 17. The processor-basedapparatus of claim 1, wherein the at least one first circuit comprises,one or more first circuits, each configured to perform a DFT on adiscrete signal of complex data symbols to obtain a first frequencyresponse vector of length M.
 18. A method for wireless communicationsutilizing an apparatus having at least one processor, comprising:performing at least one Discrete Fourier Transform (DFT) on a discretesignal of complex data symbols to obtain a first frequency responsevector of length M; performing an N-point Inverse DFT (IDFT) on a secondfrequency response vector of length N, generated from the firstfrequency response vector by inserting zero value symbols correspondingto tones not allocated to the apparatus, to obtain a vector of digitalsignal samples; pre-pending a cyclic prefix to the vector of digitalsignal samples; and generating a signal representing the vector ofdigital signal samples with pre-pended cyclic prefix for transmission.19. The method of claim 18, wherein the second frequency response vectorhas entries corresponding to one or more groups of tones allocated tothe apparatus.
 20. The method of claim 19, wherein the one or moregroups of tones allocated to the apparatus are contiguous.
 21. Themethod of claim 19, wherein the one or more groups of tones allocated tothe apparatus comprise non-contiguous groups.
 22. The method of claim21, wherein at least two of the one or more groups comprises contiguoustones within each of the at least two groups.
 23. The method of claim22, wherein the at least two groups comprise at least two groups with asame number of tones.
 24. The method of claim 21, wherein the one ormore groups comprise at least two groups with a different number oftones.
 25. The method of claim 21, wherein the non-contiguous groups oftones comprise equally spaced groups of tones.
 26. The method of claim21, wherein the non-contiguous groups of tones comprise tones separatedby tones having corresponding zero value symbols in the second frequencyresponse vector.
 27. The method of claim 26, wherein the non-contiguousgroups of tones comprise clusters of one or more tones separated bytones having corresponding zero value symbols in the second frequencyresponse vector.
 28. The method of claim 18, wherein the performing aDFT, performing an N-point IDFT and pre-pending are performed with acombination of hardware and software modules.
 29. The method of claim18, wherein at least one of the performing a DFT, performing an N-pointIDFT and pre-pending is performed utilizing a software module.
 30. Themethod of claim 18, wherein the generating comprises: converting thevector of digital signal samples to an analog signal.
 31. The method ofclaim 30, wherein the generating further comprises: modulating theanalog signal to a carrier frequency for transmission.
 32. The method ofclaim 31, wherein the generating further comprises: applying a pulsefilter to process the analog signal prior to modulation to the carrierfrequency.
 33. The method of claim 31, further comprising: amplifyingthe analog signal prior to transmission via at least one antenna.
 34. Aprocessor-based apparatus for wireless communications, theprocessor-based apparatus comprising: at least one means for performinga Discrete Fourier Transform (DFT) on a discrete signal of complex datasymbols to obtain a first frequency response vector of length M; meansfor performing an N-point Inverse DFT (IDFT) on a second frequencyresponse vector of length N, generated from the first frequency responsevector by inserting zero value symbols corresponding to tones notallocated to the apparatus, to obtain a vector of digital signalsamples; means for pre-pending a cyclic prefix to the vector of digitalsignal samples; and means for generating a signal representing thevector of digital signal samples with pre-pended cyclic prefix fortransmission.
 35. The processor-based apparatus of claim 34, wherein thesecond frequency response vector has entries corresponding to one ormore groups of tones allocated to the processor-based apparatus.
 36. Theprocessor-based apparatus of claim 35, wherein the one or more groups oftones allocated to the processor-based apparatus are contiguous.
 37. Theprocessor-based apparatus of claim 35, wherein the one or more groups oftones allocated to the processor-based apparatus comprise non-contiguousgroups.
 38. The processor-based apparatus of claim 37, wherein at leasttwo of the one or more groups comprises contiguous tones within each ofthe at least two groups.
 39. The processor-based apparatus of claim 38,wherein the at least two groups comprise at least two groups with a samenumber of tones.
 40. The processor-based apparatus of claim 37, whereinthe one or more groups comprise at least two groups with a differentnumber of tones.
 41. The processor-based apparatus of claim 37, whereinthe non-contiguous groups of tones comprise equally spaced groups oftones.
 42. The processor-based apparatus of claim 37, wherein thenon-contiguous groups of tones comprise tones separated by tones havingcorresponding zero value symbols in the second frequency responsevector.
 43. The processor-based apparatus of claim 42, wherein thenon-contiguous groups of tones comprise clusters of one or more tonesseparated by tones having corresponding zero value symbols in the secondfrequency response vector.
 44. The processor-based apparatus of claim34, wherein the means for performing a DFT, means for performing anN-point IDFT and means for pre-pending comprise a combination ofhardware and software modules.
 45. The processor-based apparatus ofclaim 34, wherein at least one of the means for performing a DFT, meansfor performing an N-point IDFT and means for pre-pending comprises asoftware module.
 46. The processor-based apparatus of claim 34, whereinthe means for generating comprises: means for converting the vector ofdigital signal samples to an analog signal.
 47. The processor-basedapparatus of claim 46, wherein the means for generating furthercomprises: means for modulating the analog signal to a carrier frequencyfor transmission.
 48. The processor-based apparatus of claim 47, whereinthe means for generating further comprises: means for applying a pulsefilter to process the analog signal prior to modulation to the carrierfrequency.
 49. The processor-based apparatus of claim 47, furthercomprising: means for amplifying the analog signal prior to transmissionvia at least one antenna.
 50. The processor-based apparatus of claim 34,wherein the at least one means for performing a Discrete FourierTransform (DFT) comprises, one or more means for performing a DFT, eachconfigured to perform a DFT on a discrete signal of complex data symbolsto obtain a first frequency response vector of length M.